Literature DB >> 33832470

A data process of human knee joint kinematics obtained by motion-capture measurement.

Jian-Ping Wang1, Shi-Hua Wang1, Yan-Qing Wang2, Hai Hu3, Jin-Wei Yu4, Xuan Zhao1, Jin-Lai Liu4, Xu Chen5, Yu Li6.   

Abstract

BACKGROUND: The motion capture has been used as the usual method for measuring movement parameters of human, and most of the measuring data are obtained by partial manual process based on commercial software. An automatic kinematics data process was developed by programming on MATLAB software in this paper.
METHODS: The motion capture measurement of healthy volunteers was carried out and the MATLAB program was used for data process. Firstly, the coordinate data of markers and anatomical points on human lower limb measured by motion capture system were read and repaired through the usual and the patch program. Meantime, the local coordinate systems of human femur and tibia were established with anatomical points. Then flexion/extension, abduction/adduction and internal/external rotation of human knee tibiofemoral joint were obtained by special coordinate transformation program.
RESULTS: Using the above methods, motion capture measurements and batch data processing were carried out on squatting and climbing stairs of 29 healthy volunteers. And the motion characteristics (flexion/extension, internal/external rotation and adduction/abduction) of the knee joint were obtained. For example, the maximum internal/external rotation in squatting and climbing stairs were respectively was 30.5 degrees and 14 degrees, etc. Meantime, the results of this paper also were respectively compared with the results processed by other research methods, and the results were basically consistent, thus the reliability of our research method was verified. After calibration processing, the compiled MATLAB program of this paper can directly be used for efficient batch processing and avoiding manual modeling one by one.
CONCLUSION: A novel Patch Program of this paper has been developed, which can make reasonable compensation for missing and noise signals to obtain more complete motion data. At the same time, a universal data processing program has also been developed for obtaining the relative movement of various components of the human body, and the program can be modified for detail special analysis. These motion capture technologies can be used to judge whether the human body functions are abnormal, provide a reference for rehabilitation treatment and design of rehabilitation equipment, and evaluate the effectiveness before and after surgery.

Entities:  

Keywords:  Kinematics; Knee joint; MATLAB; Motion capture measurement

Year:  2021        PMID: 33832470     DOI: 10.1186/s12911-021-01483-0

Source DB:  PubMed          Journal:  BMC Med Inform Decis Mak        ISSN: 1472-6947            Impact factor:   2.796


  15 in total

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Authors:  Ge Wu; Frans C T van der Helm; H E J DirkJan Veeger; Mohsen Makhsous; Peter Van Roy; Carolyn Anglin; Jochem Nagels; Andrew R Karduna; Kevin McQuade; Xuguang Wang; Frederick W Werner; Bryan Buchholz
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Authors:  K S Arun; T S Huang; S D Blostein
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4.  Modification of the Grood and Suntay Joint Coordinate System equations for knee joint flexion.

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Journal:  Med Eng Phys       Date:  2016-11-01       Impact factor: 2.242

5.  The effects of knee support on the sagittal lower-body joint kinematics and kinetics of deep squats.

Authors:  Emily Dooley; James Carr; Eric Carson; Shawn Russell
Journal:  J Biomech       Date:  2018-10-26       Impact factor: 2.712

6.  A joint coordinate system for the clinical description of three-dimensional motions: application to the knee.

Authors:  E S Grood; W J Suntay
Journal:  J Biomech Eng       Date:  1983-05       Impact factor: 2.097

Review 7.  Gait analysis: clinical facts.

Authors:  Richard Baker; Alberto Esquenazi; Maria G Benedetti; Kaat Desloovere
Journal:  Eur J Phys Rehabil Med       Date:  2016-08       Impact factor: 2.874

8.  Total knee arthroplasty for severe valgus knee deformity.

Authors:  Xinhua Zhou; Min Wang; Chao Liu; Liang Zhang; Yixin Zhou
Journal:  Chin Med J (Engl)       Date:  2014       Impact factor: 2.628

9.  Characterizing internet health information seeking strategies by socioeconomic status: a mixed methods approach.

Authors:  Susan L Perez; Richard L Kravitz; Robert A Bell; Man Shan Chan; Debora A Paterniti
Journal:  BMC Med Inform Decis Mak       Date:  2016-08-09       Impact factor: 2.796

10.  Preparing for an orthopedic consultation using an eHealth tool: a randomized controlled trial in patients with hip and knee osteoarthritis.

Authors:  Aniek A O M Claassen; Henk J Schers; Vincent J J F Busch; Petra J C Heesterbeek; Frank H J van den Hoogen; Thea P M Vliet Vlieland; Cornelia H M van den Ende
Journal:  BMC Med Inform Decis Mak       Date:  2020-05-15       Impact factor: 2.796

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